The inventions described herein relate to the field of prisoner or parolee tracking and warning systems and methods, and more specifically, to comprehensive prisoner or parolee tracking systems and methods using the Global Positioning System (xe2x80x9cGPSxe2x80x9d) to track the movements of prisoners/parolees and an expert system to continually learn, distinguish and report normal and abnormal or prohibited behavior by prisoners/parolees. Additional prisoner/parolee sensors are used to detect and report substance abuse or other alarming or threatening situations.
The control and/or confinement of prisoners/parolees is a complex and expensive problem. The ever increasing rate of various crimes requires incarceration of thousands of persons every year in the United States. Such detentions are extremely costly, requiring elaborate prison systems with attendant physical facilities and large staffs to monitor prisoner activities and to care for prisoners. Yet many crimes for which people are incarcerated do not necessarily represent a severe threat to society. Examples include selected, non-violent or minor offenses or misdemeanors, such as petty theft, shoplifting, etc. In addition, many prisoners, having served portions of prescribed sentences, could possibly be paroled if effective prisoner/parolee tracking, monitoring, and learning systems and methods were available to enable surveillance and continual detecting and learning of their activities while on parole. By restricting the areas within which parolees may move and the times that they may spend traveling or may spend at specific locations, the possibility of repeat offenses may be minimized. As a result, valuable prison space may be reserved for more serious offenders.
There is an increasing interest in remote confinement monitoring systems and methods for monitoring prisoners or parolees. Such systems typically involve a type of house arrest or house detention. Various methods have been described in issued patents for determining whether or not a prisoner or parolee is at a specified location, such as at his house. Field Monitoring Devices (FMD) are sometimes used to record information concerning prisoner or parolee presence. This information is typically transmitted to a centralized control center. Various forms of electronic monitoring technology and identification tags have been previously described for identifying prisoners or parolees and monitoring their general status or behavior. Voice verification methods have been described or taught for identifying particular prisoners or parolees to insure their presence at specified location. Secured straps and tamper-indicating fastening mechanisms that generate alarms if removal is attempted have been disclosed for attaching tags or other identification mechanisms to prisoners or parolees.
However, none of these prior art house arrest or house incarceration systems and methods are known to enable tracking, monitoring and learning of prisoners or parolees and their respective movement or behavior over extended areas nor do they verify travel routes, lengths of times given at locations, lengths of time traveling, avoidance of prohibited areas, and deviations from normal or expected behavior. Also, prior art systems are not capable of actively learning and adapting to a prisoner""s or parolee""s permissible behavior patterns and reporting deviations from those permissible patterns to a prisoner/parolee control center. Furthermore, the prior art systems do not utilize expert systems or algorithms (i.e. including but not limited to fuzzy logic, neural networks, reinforcement learning, etc.) in providing the capabilities of learning behavior, movement, or patterns of a prisoner or parolee, or of reinforcing acceptable prisoner or parolee behavior by rewarding the prisoner or parolee for proper activities. In addition, prior art prisoner tracking, monitoring, and learning systems have not fully integrated in combination together the capabilities of modem GPS technology, electronic monitoring for detecting substance abuse, and other sensors to detect unusual or suspicious events in the vicinity of prisoners or parolees being tracked and monitored.
Various house arrest, house incarceration and remote confinement systems and methods including systems with electronic monitoring, restraining mechanism, and tamper free security monitoring devices attached to prisoners or parolees are described in the following documents, each of which is incorporated herein by reference: U.S. Pat. Nos. 4,816,377; 4,918,425; 4,918,432; 4,924,211; 4,943,885; 4,952,913; 4,952,928; 4,980,671; 4,999,613; 5,023,901; 5,032,823; 5,075,670; 5,103,474; 5,117,222; 5,146,207; 5,170,426; 5,182,543; 5,204,670; 5,206,897; 5,218,344; 5,255,306; 5,266,944; 5,298,884: 5,341,126; 5,369,394; 5,448,221; 5,455,851; 5,461,390; and 5,471,197.
In addition many patents have been issued for various applications of GPS for locating and tracking objects and for navigation purpose. Various configurations of GPS-based tracking and communication systems and methods are described in the following documents, each of which is incorporated herein by reference: The Navstar Global Positioning System by Tom Logsdon, Van Nostrand and Reinhold, New York (1992), ISBN 0-422-01040-0; GPS Satellite Surveying by Alfred Leick, John Wiley and Sons, New York (1990), ISBN 0-471-81990-05; GPSxe2x80x94A Guide to the Next Utility by Jeff Hurn, Trimble Navigation, Ltd., Sunnyvale, Calif. (1989); Differential GPS Explained by Jeff Hurn, Trimble Navigation Ltd., Sunnyvale, Calif. (1993); and U.S. Pat. Nos: 5,182,566; 5,187,805; 5,202,829; 5,223,844; 5,225,842; 5,323,322; 5,243,652; 5,345,244; 5,359,332; 5,379,244; 5,382,958; 5,389,934; 5,390,125; 5,396,540; 5,408,238; 5,414,432; 5,418,537; 5,422,813; 5422,816; 5,430,656; and 5,434,787.
Furthermore, expert systems (i.e. including but not limited to fuzzy logic, neural networks, reinforcement learning, etc.) are well known to those of ordinary skill in the art, as reflected in the following publications, each of which is incorporated by reference herein: Harmon, Paul and King, David, Artificial Intelligence in Businessxe2x80x94Expert Systems, John Wiley and Sons, New York (1985), ISBN 0-471-81554-3; Gottinger, H. and Weimann, H., Artificial Intelligencexe2x80x94a tool for industry and management, Ellis Horwood, New York (1990), ISBN 0-13-048372-9; Mirzai, A. R., Artificial Intelligencexe2x80x94Concepts and applications in engineering, Chapman and Hall, New York (1990), ISBN 0-412-37900-7; Bourbakis, N., Artificial Intelligence Methods and Applications, World Scientific, New Jersey (1992), ISBN 981-02-1057-4; Schalkoff, R., Artificial Intelligence: An Engineering Approach, McGraw-Hill, New York (1990), ISBN 0-070-55084-0; Frenzel Jr., L., Crash Course in Artificial Intelligence and Expert Systems, Howard W. Sams and Co., Indianapolis, Ind. (1987), ISBN 0-672-22443-7. However, expert systems, fuzzy logic, neural networks, reinforcement learning, etc. do not appear to have been used or applied in the prisoner behavior tracking, monitoring, and learning areas.
Various techniques have also been disclosed and implemented for monitoring vital signs of persons, including breath analyzers, sweat analyzers, and heart rate monitors. However, a totally integrated prisoner/parolee monitoring and tracking system and method that makes optimum use of location, travel, and GPS tracking, physical monitoring, security system technology, and expert systems and methods is not disclosed in the prior art.
It is an object of these inventions to provide new and useful prisoner/parolee tracking, monitoring, warning, and learning and reinforcing systems and methods that permit tracking the movements of prisoners/parolees, while at the same time learning, updating and reporting unusual or prohibited travel of a prisoner/parolee.
It is a further object of these inventions to provide prisoner or parolee tracking, monitoring, warning, and learning systems and methods that make use of the existing Global Positioning System (xe2x80x9cGPSxe2x80x9d) to permit accurate determination of the location of individual prisoners/parolees.
Another object of these inventions is to provide prisoner/parolee tracking, monitoring, warning, and learning systems and methods that permit definition of specific authorized locations or destinations for each prisoner/parolee.
It is yet another object of these inventions to provide prisoner/parolee tracking, monitoring, warning, and learning systems and methods that permit comparison of travel times of a prisoner/parolee between locations with predetermined or predicted travel times to ensure that the prisoner/parolee proceeds directly between prescribed points in his or her travels.
It is another object of these inventions to provide predetermined time durations specifying a maximum permitted time that a prisoner/parolee may stay at a specific location.
It is yet another object of these inventions to permit definition of areas to which the prisoner/parolee may travel to or through to the exclusion of other areas, and to reward extended periods of good behavior with expanded areas and durations of authorized travel.
Still a further object of these inventions is to provide the above described capabilities within the context of an expert system that is capable of learning individual prisoner/parolee behavior patterns and making notes of and/or generating alarm signals only when those patterns are violated in a suspicious manner, and further, that penalizes improper behavior by restricting areas and periods of travel.
It is another object of these inventions to provide prisoner/parolee tracking, monitoring, warning, and learning systems and methods that make use of reinforcement learning whereby prisoners/parolees are rewarded for conformance to specified behavior patterns.
It is still a further object of these inventions to provide prisoner/parolee tracking, monitoring, warning, and learning systems and methods that permit simultaneous tracking of a multitude of prisoners/parolees from a prisoner/parolee control center.
Yet a further object of these inventions is to provide prisoner/parolee tracking, monitoring, warning, and learning systems and methods that permit dispatching of police or other law enforcement personnel when dangerous situations are detected that involve prisoners/parolees.
Still a further object of these inventions is to provide prisoner/parolee tracking, monitoring, warning, and learning systems and methods that enable physical monitoring of prisoners/parolees including, for example, monitoring prisoner/parolee heart rate and chemical composition of prisoner/parolee perspiration to detect excited or agitated states of prisoners/parolees or the presence of intoxicating drugs, alcohol or other substances within the prisoner""s/parolee""s body system.
Still a further object of these inventions is to provide prisoner/parolee tracking, monitoring, warning, and learning systems and methods that monitor sounds and audible signals generated by the prisoner/parolee or in the vicinity of the prisoner/parolee, and analyze those sounds for detection of dangerous situations such as gunshots.
Yet a further object of these inventions is to provide prisoner/parolee tracking, monitoring, warning, and learning systems and methods that permit transmission of spoken commands from a prisoner/parolee control center to individual prisoners/parolees directing them to return to prescribed locations or travel patterns, and to warn those prisoners/parolees that they have violated their predetermined movement, travel, or other conditions of parole.
Still a further object of these inventions is to provide warning to the general population within areas that may be threatened by individual prisoners or parolees that have violated their prescribed travel space or behavior restrictions.
Yet another object of these inventions is to provide prisoner tracking, monitoring, warning, and learning systems and methods that make use of prisoner sensor processing units that are securely attached to the prisoner in a manner that cannot be removed without generating warning signals.
Further objects of the invention are apparent from reviewing the summary of the invention, detailed description, and claims which are set forth below.
The above and other objects are achieved by a method of monitoring and learning a subject""s behavior. A first file including reference behavior data defining several classes of individuals to be monitored is created and stored in a memory of a monitoring station computer. Included within that file is data relating to at least one class to which the subject belongs. A second file including behavior data defining the subject to be monitored is also created and stored in the monitoring station computer memory. The monitoring station computer is defined and programmed with data defining a set of allowed activities for each of the several classes of individuals to be monitored. The monitoring station computer is also defined and programmed with data defining a set of allowed activities that are specific for the subject to be monitored. These allowed activities include predefined routes and times of travel in a location remote from the monitoring station computer. A remote monitoring transmitter and receiver is attached to the subject. The receiver cooperates with a satellite global positioning system to determine the subject""s current location as the subject moves about in the area located remote from the monitoring station computer. Data defining the subject""s location at a specific time is periodically transmitted from the remote monitoring transmitter and receiver to the monitoring station computer. The data transmitted from the remote monitoring transmitter is analyzed by the computer by comparing the data defining the subject""s current location and time with the set of allowed activities that are specific for the subject. The computer determines if there are any variations from the allowed activities. A first alarm signal is generated defining any determined variation from the allowed activities. An expert system is used to further analyze the first alarm signal defining the determined variation from the allowed activities. This expert system is programmed to recognize a continuum of degrees of alarms based on a comparison of the determined variation, the behavior data defining the subject to be monitored, and the reference behavior data defining the class of individuals to which the subject belongs. The expert system also generates a second alarm signal defining a specific recommended course of action that is appropriate for the determined variation, the subject""s specific behavior data, and the data defining the class of individuals to which the subject belongs. Hereafter, the phrase prisoners or parolees are used interchangeably and may just as easily be used for children, incompetent persons, or the aged.
Furthermore, the data defining the subject""s current location and time, the set of allowed activities that are specific for the subject, and the second alarm signal defining the recommended course of action are more frequently analyzed. Based on this more frequent analysis, it is determined whether the second alarm condition has changed by becoming more or less critical. If necessary, the second alarm condition is modified to reflect any determined change.
The reference behavior data defining several classes of individuals to be monitored includes but is not limited to criminal behavior data, criminal history and criminal record data, parole level information, data relating to a number of different types of crimes, data relating to a defined deviated behavior standard derived, and crime probability data that compares various crime types with various location types wherein a crime probability for each of the various crime types is determined and assigned for each of the various location types. The behavior data defining the subject to be monitored includes but is not limited to criminal behavior data, criminal history and criminal record data, parole level information, and data relating to types of crimes committed by the subject. The data defining a set of allowed activities for each of the several classes of individuals to be monitored includes but is not limited to permitted travel data, permitted location data, permitted location dwell time data, and permitted travel path data.
Also, the remote monitoring transmitter and receiver has an audible alarm. A signal is transmitted from the monitoring station computer to the monitoring transmitter and receiver attached to the subject. The signal activates the audible alarm to indicate to the subject that an alarm condition has been triggered. An expert system is operated to analyze the first and second alarm conditions and the data that generated the alarm conditions. The first and second data files are modified to reflect learned activities that either should or should not generate an alarm. The expert system learns behavior that unnecessarily generated an alarm. The behavior data defining the subject to be monitored and the data defining the set of allowed activities that are specific for the subject to be monitored are accordingly modified so that the alarm is not generated in the future.
Periodic monitoring of the subject""s behavior continues. After a predefined period without an alarm being generated, the data defining the set of allowed activities that are specific for the subject to be monitored is modified to provide for an increased area and longer allowed time of travel. The increase area and longer time of travel is accordingly communicated to the remote monitoring transmitter and receiver attached to the subject. After an alarm is generated, the data defining the set of allowed activities that are specific for the subject to be monitored is modified to provide for a decreased area and shorter time of travel. The decreased area and shorter allowed time of travel is accordingly communicated to the remote monitoring transmitter and receiver attached to the subject.
The remote monitoring transmitter and receiver attached to the subject is used to monitor a physical attribute of the subject. Data defining the monitored physical attribute of the subject is transmitted from the remote monitoring transmitter and receiver to the monitoring station computer. The computer analyzes the data by comparing the data defining the subject""s monitored location, time and physical attributes with the set of allowed activities that are specific for the subject. The computer determines if there are any variations from these allowed activities. The physical attributes being monitored include but are not limited to speech, alcoholic levels, heart rate, breath and perspiration.
The above and other objects are also achieved by a system of monitoring and learning a subject""s behavior. The system includes at least a monitoring station computer, a remote monitoring transmitter and receiver, and an expert system. The monitoring station computer creates and stores in its memory a first file including reference behavior data defining several classes of individuals to be monitored. Included within that file is data relating to at least one class to which the subject belongs. The monitoring station computer also creates and stores in its memory a second file including behavior data defining the subject to be monitored is also created and stored in the monitoring station computer memory. The monitoring station computer is defined and programmed with data defining a set of allowed activities for each of the several classes of individuals to be monitored. The monitoring station computer is also defined and programmed with data defining a set of allowed activities that are specific for the subject to be monitored. These allowed activities include predefined routes and times of travel in a location remote from the monitoring station computer. The remote monitoring transmitter and receiver is attached to the subject. The receiver cooperates with a satellite global positioning system to determine the subject""s current location as the subject moves about in the area located remote from the monitoring station computer. Data defining the subject""s location at a specific time is periodically transmitted from the remote monitoring transmitter and receiver to the monitoring station computer. The data transmitted from the remote monitoring transmitter is analyzed by the monitoring computer by comparing the data defining the subject""s current location and time with the set of allowed activities that are specific for the subject. The monitoring computer determines if there are any variations from the allowed activities. A first alarm signal is generated by the monitoring computer defining any determined variation from the allowed activities. The expert system is used to further analyze the first alarm signal defining the determined variation from the allowed activities. This expert system is programmed to recognize a continuum of degrees of alarms based on a comparison of the determined variation, the behavior data defining the subject to be monitored, and the reference behavior data defining the class of individuals to which the subject belongs. The expert system also generates a second alarm signal defining a specific recommended course of action that is appropriate for the determined variation, the subject""s specific behavior data and the data defining the class of individuals to which the subject belongs.